The Journal of Ambient Intelligence and Smart Environments (JAISE) serves as a forum to discuss the latest developments on Ambient Intelligence (AmI) and Smart Environments (SmE). Given the multi-disciplinary nature of the areas involved, the journal aims to promote participation from several different communities covering topics ranging from enabling technologies such as multi-modal sensing and vision processing, to algorithmic aspects in interpretive and reasoning domains, to application-oriented efforts in human-centered services, as well as contributions from the fields of robotics, networking, HCI, mobile, collaborative and pervasive computing. This diversity stems from the fact that smart environments can be defined with a variety of different characteristics based on the applications they serve, their interaction models with humans, the practical system design aspects, as well as the multi-faceted conceptual and algorithmic considerations that would enable them to operate seamlessly and unobtrusively.

The Journal of Ambient Intelligence and Smart Environments will focus on both the technical and application aspects of these.

Abstract: An approach is presented for flexible management of smart homes, covering both home automation and telecare. The aim is to allow end users to manage their homes without requiring detailed technical knowledge or programming ability. This is achieved at three levels: managing home components and their interactions, stating policies for how the home system should react to events, and defining high-level goals for what the user wishes to achieve. The component architecture is based on OSGi (Open Services Gateway initiative). Policies and goals are formulated in the APPEL language (Adaptable and Programmable Policy Environment and Language), and supported by the…ACCENT policy system (Advanced Component Control Enhancing Network Technologies). At run-time, high-level goals lead to selection of an optimal and conflict-free set of policies. These in turn determine how the home should react to various events. The paper closes with an evaluation of the approach from the points of view of functionality and usability.
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Abstract: Ambient Intelligence (AmI) research is giving birth to a multitude of futuristic home scenarios and applications; however a clear discrepancy between current installations and research-level designs can be easily noticed. Whether this gap is due to the natural distance between research and engineered applications or to mismatching of needs and solutions remains to be understood. This paper discusses the results of a survey about user expectations with respect to intelligent homes. Starting from a very simple and open question about what users would ask to their intelligent homes, we derived user perceptions about what intelligent homes can do, and we…analyzed to what extent current research solutions, as well as commercially available systems, address these emerging needs. Interestingly, most user concerns about smart homes involve comfort and household tasks and most of them can be currently addressed by existing commercial systems, or by suitable combinations of them. A clear trend emerges from the poll findings: the technical gap between user expectations and current solutions is actually narrower and easier to bridge than it may appear, but users perceive this gap as wide and limiting, thus requiring the AmI community to establish a more effective communication with final users, with an increased attention to real-world deployment.
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Abstract: A key aspect of ubiquitous computing is using sensor networks to effectively and unobtrusively infer human activities in their environment. A typical top-down approach is to first label and decompose activities as sequences of actions with certain probabilities, and then use these predefined activity models for recognition and prediction. This approach, however, does not capture the internal goals of different actions, and it only deals with those explicitly defined activity models. In this article, inspired by traditional activity theory and qualitative process theory, we present a goal-directed human activity computing model. A formal activity ontology is proposed so as to…capture the internal semantic relations between different atomic activities such as actions and processes. A number of representative inference rules are then introduced to predict the future activities based on the activity ontology. The proposed formal activity computing model is simulated and demonstrated with Maude, a formal specification and programming language.
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Abstract: Advances in computer vision and pattern recognition research are leading to video surveillance systems with improved scene analysis capabilities. However, up to now few works have handled the problem of how the system, along with a human operator, can actively cope with detected anomalous events. In this paper, on the basis of recent studies on artificial cognitive systems, a general framework is proposed for designing interactive, adaptable and intelligent surveillance systems. The aim of the system is to react to situations in a preventive way using actuators installed in the monitored environment. An application of the proposed system is introduced…where a guard is supported in pursuing an intruder. The operator is first localized and tracked and then multi-modal guidance messages are communicated to him on a mobile device. Previous experience on the interaction dynamics between the two players is provided by a simulator, modeling guard and intruder behaviors, to predict near future events and decide the appropriate messages to be sent. Results on real world video sequences show the reliability of the simulated data to build up interaction models and predict near future events. Moreover, the system capability of learning relationships with the operator to establish efficient and personalized communications is verified.
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Abstract: In-home monitoring of gait velocity with passive PIR sensors in a smart home has been shown to be an effective method of continuously and unobtrusively measuring this important predictor of cognitive function and mobility. However, passive measurements of velocity are nonspecific with regard to who generated each measurement or walking event. As a result, this method is not suitable for multi-person homes without additional information to aid in the disambiguation of gait velocities. In this paper we propose a method based on Gaussian mixture models (GMMs) combined with infrequent clinical assessments of gait velocity to model in-home walking speeds of…two or more residents. Modeling the gait parameters directly allows us to avoid the more difficult problem of assigning each measured velocity individually to the correct resident. We show that if the clinically measured gait velocities of residents are separated by at least 15 cm/s a GMM can be accurately fit to the in-home gait velocity data. We demonstrate the accuracy of this method by showing that the correlation between the means of the GMMs and the clinically measured gait velocities is 0.877 (p value < 0.0001) with bootstrapped 95% confidence intervals of (0.79, 0.94) for 54 measurements of 20 subjects living in multi-person homes. Example applications of using this method to track in-home mean velocities over time are also given.
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Abstract: The book “Safeguards in a world of ambient intelligence” is unique in its kind. It discusses social, economic, legal, technological and ethical issues related to identity, privacy and security in Ambient Intelligence (AmI). It introduces AmI and, subsequently, makes it vivid by describing four scenarios. Threats and vulnerabilities as well as safeguards are identified, which stress the already common aspects of current IT and AmI. The book is a little EU-biased but is otherwise well balanced and excellently structured.